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ETL Developer / Data Engineer

Posted today

neshent technologiesAddison (TX)

SENIORITY

Senior

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About the role

Key Responsibilities: Design, develop, and maintain ETL processes and scalable data pipelines for enterprise data integration. Build data ingestion and transformation workflows using Java and/or Python. Develop and integrate REST APIs to support data exchange between applications and enterprise systems. Write, optimize, and maintain SQL queries for data extraction, transformation, validation, and performance tuning. Work with Oracle, Snowflake, and/or PostgreSQL databases to support data storage, processing, and integration requirements. Implement data quality checks, error handling, logging, and monitoring to ensure data accuracy and pipeline reliability. Troubleshoot data pipeline failures, integration issues, and database performance bottlenecks. Collaborate with data engineers, application developers, architects, and business stakeholders to deliver reliable data solutions. Follow established coding standards, version control practices, and deployment procedures. Support CI/CD processes and contribute to the continuous improvement of data engineering workflows.
Required Qualifications: Strong programming experience in Java and/or Python. Hands-on experience developing and maintaining ETL processes and data pipelines in enterprise environments. Practical experience working with REST APIs for data ingestion and system integration. Strong SQL skills, including data transformation, complex queries, and performance tuning. Experience with Oracle and/or Snowflake/PostgreSQL databases. Understanding of data integration patterns, data processing workflows, and data quality principles. Strong analytical, problem-solving, and troubleshooting skills. Ability to collaborate effectively with technical teams in a fast-paced enterprise environment. Preferred Experience Familiarity with CI/CD tools and practices, including Jenkins, Git, and Bitbucket. Knowledge of data ingestion frameworks and enterprise integration tools. Experience working with Snowflake-based data platforms and modern data pipeline architectures. Familiarity with automated deployment processes, version control, and software development best practices. Experience supporting cloud-based or enterprise-scale data engineering solutions.

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